Generative Development Framework
GDF.ai
  • Intro to GDF-FSE
    • Generative AI, Large Language Models, ChatGPT?
    • Knowledge Areas
    • Access a Chat Based LLM
    • Why GDF?
    • Expectations
  • Limitations
  • Prompting
    • Prompt Patterns
    • Prompt Context
    • Prompt Stores
    • Prompt Operators
    • Prompt Chaining
  • Security
    • Protecting Data
    • Protecting Application Security
    • Protecting Intellectual Property
    • Protection Stores
    • AI Security Assessments and Penetration Testing
    • Social Engineering Testing with AI
  • Subject Knowledge Areas
    • Ideation
      • Identifying a Problem Statement
      • Plan and Prioritize Features
      • Develop User Stories
      • Requirement Gathering
      • Ideation Prompting
      • Ideation Template
    • Specification
      • Specifying Languages
      • Specifying Libraries
      • Specifying Project Structures
      • Specify Schemas
      • Specifying Elements
      • Specifying API Specs
    • Generation
      • Generating UI Elements
      • Generating Mock Data
      • Generating Schemas
      • Generating Parsers
      • Generating Databases
      • Generate Functions
      • Generate APIs
      • Generate Diagrams
      • Generating Documentation
    • Transformation
      • Converting Languages
      • Converting Libraries
    • Replacement
      • Replacing Functions
      • Replacing Data Types
    • Integration
      • Connecting UI Components
      • Connecting UI to Backend
      • Connecting Multiple Services Together
      • Connecting Cloud Infrastructure (AWS)
    • Separation
      • Abstraction
      • Model View Controller (MVC)
    • Consolidation
      • Combining UI Elements
      • Deduplicating Code Fragments
    • Templating
      • Layouts
      • Schemas
      • Project Structures
      • Content Management Systems
    • Visualization
      • General Styling
      • Visual Referencing
      • Visual Variations
    • Verification
      • Test Classes
      • Logging and Monitoring
      • Automated Testing
      • Synthetic Monitoring
    • Implementation
      • Infrastructure
      • DevOps / Deployment
    • Optimization
      • General Optimization
      • Performance Monitoring
      • Code Review
  • Guidance
    • Business Process
    • Regulatory Guidance
  • Generative Pipelines
  • Troubleshooting
    • Client Side Troubleshooting
    • Server Side Troubleshooting
    • Troubleshooting with AI
    • Documentation
    • Infrastructure Engineering
  • Terminology
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  • Puppeteer
  • Example: Synthetic Monitoring for User Journeys
  • Prompt
  • Response

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  1. Subject Knowledge Areas
  2. Verification

Synthetic Monitoring

Simulating end users through synthetic monitoring and how generative AI can help

Synthetic monitoring, also known as active monitoring, is a type of monitoring that simulates user interactions with an application or website to test its availability, performance, and functionality. In other words, synthetic monitoring uses automated scripts or tools to perform predefined actions on an application or website, and measure the response time and behavior of the application.

In the context of JavaScript, synthetic monitoring can be used to test the performance and availability of web applications and websites. Here are some examples of tools and frameworks that can be used for synthetic monitoring in JavaScript:

Puppeteer

Puppeteer is a Node.js library that provides a high-level API for controlling headless Chrome or Chromium browsers. It can be used to write automated tests and perform synthetic monitoring of web applications and websites. Puppeteer allows you to navigate to pages, interact with elements, and measure performance metrics like page load time and time to first paint.

Example: Synthetic Monitoring for User Journeys

Synthetic monitoring involves simulating user journeys through an application to ensure its functionality and performance. By using generative AI to create user journey tests, you can ensure that the application works as expected and delivers a seamless user experience.

Prompt

prompt
Write a Puppeteer script in Node.js that simulates a user journey on a bicycle rental app, including searching for a mountain bike, adding it to the cart, filling in the {checkout_form_form}, and submitting the order. Make sure to validate that the cart updates and the order confirmation is displayed.

Response

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();
  await page.goto('http://localhost:3000/bicycle-rental-app');

  // Simulate user journey: Search for a bicycle, view details, and add to cart
  await page.type('input[name=search]', 'mountain bike');
  await page.click('button[type=submit]');
  await page.waitForSelector('.bicycle-list-item');
  await page.click('.bicycle-list-item');
  await page.waitForSelector('.bicycle-details');
  await page.click('button.add-to-cart');

  // Check that the cart has been updated
  const cartItems = await page.$eval('.cart-items', (el) => el.textContent);
expect(cartItems).toContain('1');

// Continue user journey: Proceed to checkout and fill in the form
await page.click('button.proceed-to-checkout');
await page.waitForSelector('.checkout-form');
await page.type('input[name=name]', 'John Doe');
await page.type('input[name=email]', 'john.doe@example.com');
await page.type('input[name=address]', '123 Main St');
await page.type('input[name=city]', 'New York');
await page.type('input[name=state]', 'NY');
await page.type('input[name=zip]', '10001');
await page.click('button[type=submit]');

// Verify that the order has been submitted successfully
await page.waitForSelector('.order-confirmation');
const orderConfirmation = await page.$eval('.order-confirmation', (el) => el.textContent);
expect(orderConfirmation).toContain('Thank you for your order!');

await browser.close();
})();

In this example, Puppeteer is used to simulate a user journey through a bicycle rental application. The test searches for a bicycle, views its details, adds it to the cart, proceeds to checkout, fills in the form, and submits the order. The test then checks that the order has been successfully submitted.

By integrating generative AI into the software development lifecycle and using it for automated testing, developers can ensure the reliability, performance, and security of their applications. This approach not only saves time and effort, but also helps maintain high-quality code and reduces the likelihood of introducing bugs and vulnerabilities.

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Last updated 3 months ago

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